Tools

Reproducible Research Promotion

Why?

Les cartes, comme les autres productions graphiques ou statistiques sont des éléments à parts entières des études scientifiques.

Giraud and Lambert (2017)

La plupart des cartes produites dans un contexte académique sont issues de processus complexes.
Elles sont souvent produites en utilisant une grande variété de logiciels et de formats.

Cette variété de formats et de logiciels rend difficile la reproduction des cartes.

Simplifier les chaines de traitement pour couvrir les différentes étapes de la construction cartographique.

How?

sf, corner stone of the R spatial ecosystem

Pebesma and Bivand (2020)

mf_map()

mf_map() is the main function of the package.

mf_map(x = objet_sf,
       var = "variable",
       type = "map type",
       ...)

?mapsf

9 map types

Vignette : Get started

Map mayout

Example

• Base map:

mtq <- mf_get_mtq()
# Plot the base map
mf_map(x = mtq)

• Choropleth map with default parameters:

mtq <- mf_get_mtq()
# Plot a choropleth map
mf_map(x = mtq, var = "MED", type = "choro")

• Parameters customisation:

mtq <- mf_get_mtq()
# Plot a choropleth map
mf_map(x = mtq, var = "MED", type = "choro",
       pal = "Dark Mint",
       breaks = "quantile",
       nbreaks = 6,
       leg_title = "Median Income\n(euros)",
       leg_val_rnd = -2,
       leg_pos = "topright")

• Map layout:

mtq <- mf_get_mtq()
# Plot a choropleth map
mf_map(x = mtq, var = "MED", type = "choro",
       pal = "Dark Mint",
       breaks = "quantile",
       nbreaks = 6,
       leg_title = "Median Income\n(euros)",
       leg_val_rnd = -2,
       leg_pos = "topright")
# Plot a layout elements
mf_title("Wealth in Martinique, 2015")
mf_credits("T. Giraud\nSources: INSEE & IGN, 2018")
mf_scale(size = 5)
mf_arrow('topleft')

• Theme:

mtq <- mf_get_mtq()
# Start a map using a theme
mf_init(x = mtq, theme = "dark")
# Plot a choropleth map
mf_map(x = mtq, var = "MED", type = "choro",
       pal = "Dark Mint",
       breaks = "quantile",
       nbreaks = 6,
       leg_title = "Median Income\n(euros)",
       leg_val_rnd = -2,
       leg_pos = "topright",
       add = TRUE)
# Plot a layout elements
mf_title("Wealth in Martinique, 2015")
mf_credits("T. Giraud\nSources: INSEE & IGN, 2018")
mf_scale(size = 5)
mf_arrow('topleft')

• Shadow:

mtq <- mf_get_mtq()
# Start a map using a theme
mf_init(x = mtq, theme = "dark")
# Plot a shadow
mf_shadow(mtq, col = "grey10", add = TRUE)
# Plot a choropleth map
mf_map(x = mtq, var = "MED", type = "choro",
       pal = "Dark Mint",
       breaks = "quantile",
       nbreaks = 6,
       leg_title = "Median Income\n(euros)",
       leg_val_rnd = -2,
       leg_pos = "topright",
       add = TRUE)
# Plot a layout elements
mf_title("Wealth in Martinique, 2015")
mf_credits("T. Giraud\nSources: INSEE & IGN, 2018")
mf_scale(size = 5)
mf_arrow('topleft')

• Inset

mtq <- mf_get_mtq()
# Start a map using a theme
mf_init(x = mtq, theme = "dark")
# Plot a shadow
mf_shadow(mtq, col = "grey10", add = TRUE)
# Plot a choropleth map
mf_map(x = mtq, var = "MED", type = "choro",
       pal = "Dark Mint",
       breaks = "quantile",
       nbreaks = 6,
       leg_title = "Median Income\n(euros)",
       leg_val_rnd = -2,
       leg_pos = "topright",
       add = TRUE)
# Add an inset world map
mf_inset_on(x = "worldmap", pos = "right")
mf_worldmap(mtq, col = "#0E3F5C")
mf_inset_off()
# Plot a layout elements
mf_title("Wealth in Martinique, 2015")
mf_credits("T. Giraud\nSources: INSEE & IGN, 2018")
mf_scale(size = 5)
mf_arrow('topleft')

• Extanded margins

mtq <- mf_get_mtq()
# Start a map using a theme and extra margins
mf_init(x = mtq, theme = "dark",
        expandBB = c(0,0,0,.3))
# Plot a shadow
mf_shadow(mtq, col = "grey10", add = TRUE)
# Plot a choropleth map
mf_map(x = mtq, var = "MED", type = "choro",
       pal = "Dark Mint",
       breaks = "quantile",
       nbreaks = 6,
       leg_title = "Median Income\n(euros)",
       leg_val_rnd = -2,
       leg_pos = "topright",
       add = TRUE)
# Add an inset world map
mf_inset_on(x = "worldmap", pos = "right")
mf_worldmap(mtq, col = "#0E3F5C")
mf_inset_off()
# Plot a layout elements
mf_title("Wealth in Martinique, 2015")
mf_credits("T. Giraud\nSources: INSEE & IGN, 2018")
mf_scale(size = 5)
mf_arrow('topleft')

Insets

Vignette : How to Create Inset Maps

• With a geographic object

mf_map(mtq)
mf_inset_on(x = mtq[1, ], 
            cex = .3)
mf_map(mtq[1, ])
mf_inset_off()

• Location inset

mf_map(mtq)
mf_inset_on(x = "worldmap", 
            pos = "bottomleft")
mf_worldmap(x = mtq)
mf_inset_off()

• Non-cartographic inset

library(mapsf)
library(beeswarm)
mtq <- mf_get_mtq()
# create classes
bks <- mf_get_breaks(x = mtq$MED, nbreaks = 4, 
                     breaks = "quantile") 
bks <- round(bks, digits = -2)
# define a color palette
pal <- hcl.colors(n = 4, palette = "Burg", rev = TRUE)
# set a theme
mf_theme("candy")
mf_export(x = mtq, filename = "img/insetbee.svg",
          export = "svg", 
          width = 7,theme = "candy")
fg <-mf_theme()$fg
# Create the map
mf_map(x = mtq, var = "MED", type = "choro",
       pal = pal, breaks = bks, leg_pos = NA)
# start the inset
mf_inset_on( fig = c(0.6, .99, 0.86, .99))
# draw the histogram
par(mar = c(0,0,1.7,0))
beeswarm(mtq$MED, vertical = FALSE, cex =1.2, 
         spacing = .95, axes = FALSE, 
         pwcol = pal[findInterval(mtq$MED, bks)], 
         ylim = c(-1,3), pch = 20)
axis(side = 1, at = bks, las = 2, tick = FALSE, 
     line = -1, cex.axis = .7, col.axis = fg)
abline(v=bks, lwd = .5, lty = 3, col = fg)
title("Median Income\nin euros", cex.main = .8, 
      col.main = fg, font.main = 1, adj = 0)
# close the inset
mf_inset_off()
# Add map layout
mf_title("Wealth in Martinique, 2015", pos = "left")
mf_scale(5)
mf_credits(paste0("Sources: Insee and IGN, 2018\n",
                  "mapsf ", packageVersion("mapsf")))
dev.off()

Themes

Vignette : How to Use Themes

Raster

library(maptiles)
mtq <- st_transform(mtq, 3857)
osm <- get_tiles(
  mtq, 
  provider = "Stamen.TerrainBackground", 
  crop= TRUE, 
  zoom = 11
)
th <- mf_theme(
  x = "default", bg = "#99b3cc", 
  inner = TRUE, line = 1.5, cex = 1, 
  pos = "right", mar = c(0,0,0,0)
)
mf_export(x = osm, filename = "img/osm.png", 
          width = 672, theme = th, res = 150)
mf_raster(osm)
mf_map(mtq, col = NA, add = TRUE)
mf_scale()
mf_title("mf_raster()")
mf_credits(get_credit("Stamen.TerrainBackground"))
dev.off()

Documentation

• A website

• A ‘Get started’ vignette.

• ‘How to’ vignettes:

  • How to create faceted maps
  • How to create inset maps
  • How to export maps
  • How to use a custom font family
  • How to use themes

• A cheat sheet

Development

A minimal number of well-known dependancies:

• CI/CD with GitHub Actions

• Tests with tinytest, coverage with Codecov

• Informative commit messages with conventional commits

tanaka

Also called “relief contours method,” “illuminated contour method” or “shaded contour lines method,” the Tanaka method enhances the representation of topography on a map by using shaded contour lines. The result is a 3D-like map.

This package is a simplified implementation of the Tanaka method, north-west white contours represent illuminated topography and south-east black contours represent shaded topography.

library(tanaka)
library(elevatr)
# use elevatr to get elevation data
ras <- get_elev_raster(
  locations = data.frame(x = c(6.7, 7), y = c(45.8,46)),
  z = 10, prj = "EPSG:4326", clip = "locations"
)
# display the map
opar <- par(mar = c(0,3,0,0))
tanaka(x = ras, breaks = seq(500,4800,250), 
       col = hcl.colors(18,"Inferno"))
par(opar)

Tanaka also can be used with non-topographical data:

linemap

linemap() displays a map made of lines using a data frame of gridded data.

library(linemap)
library(mapsf)
data("popOcc")
occitanie <- st_read(system.file("gpkg/geofla.gpkg", 
                                 package = "linemap"), 
                     layer = "Occitanie")
th <- mf_theme(bg = "ivory2")
mf_export(occitanie, width = 800, filename = "img/linemap.png")
mf_map(occitanie, col="ivory1", border = NA)
linemap(x = popOcc, var = "pop", k = 3.25, threshold = 50,
        col = "ivory1", border = "ivory4", lwd = 0.6, add = TRUE)
mf_title("Population in Occitanie")
mf_credits("Gridded data 1 km, INSEE 2010")
dev.off()

maptiles

To create maps from tiles, maptiles downloads, composes and displays tiles from a large number of providers (e.g. OpenStreetMap, Stamen, Esri, CARTO, or Thunderforest).

library(sf)
library(maptiles)
hop <- st_read("data/hospital.gpkg", layer = "hospital")
osm <- get_tiles(hop)
th <- mf_theme(mar = c(0,0,0,0), inner = TRUE, line = 2, cex = 1.8)
mf_export(osm, filename = "img/maptiles.png", 
          width = 768, theme = th)
mf_raster(osm, add = TRUE)
mf_map(hop, "capacity", "prop", 
       border = "grey", inches = .4,
       leg_title = "Number of beds", 
       leg_frame = TRUE)
mf_title("Public Hospital Capacities in Paris")
mf_credits(get_credit("OpenStreetMap"), bg = "#ffffff80")
dev.off()

The following figure shows mini maps for most of the tiles providers available:

popcircle

This one-function package computes circles with areas scaled to a variable and displays them using a compact layout (higher values in the center, lower values at the periphery). Original polygons are scaled to fit inside these circles (size are roughly proportional, not strictly).

spikemap

It is possible to map quantities with circles, squares or other simple geometric symbols, spikemap uses spikes.

library(sf)
library(spikemap)
library(mapsf)
# import the dataset from the package
com <- st_read(system.file("gpkg/com.gpkg", package="spikemap"), 
               quiet = TRUE)
mf_map(com, lwd =.2)
spikemap(x = com, var = "pop")